Ideas and Insight supporting all stages of Drug Discovery & Development

The “vigilance” aspect of the pharmacovigilance process can
be very challenging. Always being on guard and knowing all of the places to
look can be difficult. In a sea of information, it can even seem like a nearly
impossible task to maintain awareness of all adverse events (AE). That is why
there has been a lot of buzz around technologies that can help automate parts
of the pharmacovigilance process.

Beginning a new year offers an important
opportunity to reflect on the past one. I’ve been thinking a lot about what I
learned in 2019, and where I believe my industry is going as we continue
further into 2020.

Machine learning for predicting chemistry is an area of intense research and publication. However, since the terminology used to describe this activity is diverse it can be difficult to identify all of the publications describing use of computers to predict chemical outcomes or retrosynthesis paths.